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venv/lib/python3.9/site-packages/mlflow/recipes/__init__.py

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+"""
+
+.. warning::
+
+    MLflow Recipes is deprecated and will be removed in a future release.
+
+MLflow Recipes is a framework that enables you to quickly develop high-quality models and deploy
+them to production. Compared to ad-hoc ML workflows, MLflow Recipes offers several major benefits:
+
+- **Recipe templates**: `Predefined templates <../../recipes/index.html#recipe-templates>`_ for
+  common ML tasks, such as `regression modeling <../../recipes/index.html#regression-template>`_,
+  enable you to get started quickly and focus on building great models, eliminating the large amount
+  of boilerplate code that is traditionally required to curate datasets, engineer features, train &
+  tune models, and package models for production deployment.
+
+- **Recipe engine**: The intelligent recipe execution engine accelerates model development by
+  caching results from each step of the process and re-running the minimal set of steps as changes
+  are made.
+
+- **Production-ready structure**: The modular, git-integrated `recipe structure
+  <../../recipes/index.html#recipe-templates-key-concept>`_ dramatically simplifies the handoff from
+  development to production by ensuring that all model code, data, and configurations are easily
+  reviewable and deployable by ML engineers.
+
+For more information, see the `MLflow Recipes overview <../../recipes/index.html>`_.
+"""
+
+from mlflow.recipes.recipe import Recipe
+
+__all__ = ["Recipe"]